Distributed Networked Control Systems (D-NCS) have been at the core of national critical infrastructures and industrial control systems for many decades (e.g., electrical power systems and transportation systems). While most D-NCS have been safe in the past, a few confirmed cases of cyber attacks have occurred. The recent presence of the infamous industrial control system malwares “Stuxnet” and “Flame” have brought significant attention to making industrial control systems safe from such malicious cyber attacks. Many D-NCS applications are time-sensitive, data-sensitive, and safety-critical. The potential consequences of compromising D-NCS can be devastating to public health and safety, national security, and the economy. Therefore, it is important to implement D-NCS with secure controls that make reliable, safe, and flexible performance possible.
D-NCS are increasingly more vulnerable to cyber attacks with the rapid advancements and uses of networking, embedded systems, wireless communication technologies, and novel control strategies. In particular, more and more distributed control algorithms are being used in D-NCS because of their flexibility, robustness, computation, and communication features. These algorithms, however, increase the vulnerability of D-NCS to malicious cyber attacks. In the absence of a centralized supervisory node that monitors the activities of the nodes in the network, distributed control strategies are prone to cyber attacks and component failures. Thus, it is increasingly important to guarantee that computations are secure and trustworthy even in the presence of misbehaving devices. Also, most of the current efforts for protecting D-NCS have been accomplished by prevention and are limited to communication security. There is an urgent growing need to protect control algorithms from malicious cyber attack.
One typical task in the NCS is to agree upon a certain performance measure for a group of agents, such as the work load on a network of parallel computers, the clock speed for wireless sensor networks, or the velocity or formation pattern for a group of autonomous vehicles. Several distributed control algorithms, such as consensus algorithms and gossip algorithms, have been proposed and studied in D-NCS to accomplish such tasks (e.g., formation control of multi-robot systems, time synchronization of wireless sensor networks). However, there is a need for improvements on reaching agreement in the presence of misbehaving agents.
In view of the foregoing, there is a continuing need for improved systems and techniques for securing D-NCS and other systems.